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- Vol. 6 Issue 6
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AI-Based Sign Language Recognition and Translation System
Authors
1 Professor, Department of Information Science and Engineering, Bapuji Institute of Engineering and Technology, Davangere, Karnataka, India. 2 3 4 5 Department of Information Science and Engineering, Bapuji Institute of Engineering and Technology, Davangere, Karnataka, India.
Article Information
- Published In
- Volume 6, Issue 6 (2026)
- Published Online
- November-December 2026
- Pages
- 56-61
- Article Type
- Original Article
- Check for updates
-
References
1. A. Khan, S. Jin, G.-H. Lee, G. E. Arzu, L. Minh Dang, T. N. Nguyen, W. Choi, and H. Moon, “Deep Learning Approaches for Continuous Sign Language Recognition: A Comprehensive Review,” IEEE Access, vol. 13, pp. 55524–55544, 2025. DOI: 10.1109/ACCESS.2025.3554046.
2. N. C. Camgoz, O. Koller, S. Hadfield, and R. Bowden, “Sign Language Transformers: Joint End-to-End Sign Language Recognition and Translation,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, pp. 10023–10033. DOI: 10.1109/CVPR42600.2020.01004.
3. S. Tan, N. Khan, Z. An, Y. Ando, R. Kawakami, and K. Nakadai, “A Review of Deep Learning-Based Approaches to Sign Language Processing,” Advanced Robotics, vol. 38, no. 23, pp. 1649–1667, 2024. DOI: 10.1080/01691864.2024.2442721. SQLAlchemy Authors, “SQLAlchemy Documentation.”
4. Z. Yu, S. Huang, Y. Cheng, and T. Birdal, “SignAvatars: A Large-scale 3D Sign Language Holistic Motion Dataset and Benchmark,” in Proceedings of the European Conference on Computer Vision (ECCV), 2024. OpenRouter, “OpenRouter Documentation.”
5. A. Núñez-Marcos, O. Perez-de-Viñaspre, and G. Labaka, “A Survey on Sign Language Machine Translation,” Expert Systems with Applications, vol. 213, article 118993, 2023. DOI: 10.1016/j.eswa.2022.118993. N. Reimers and I. Gurevych, “Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks,” in Proceedings of EMNLP-IJCNLP, 2019, pp. 3982–3992. DOI: 10.18653/v1/D19-1410.
6. D. D. Chakladar, P. Kumar, S. Mandal, P. P. Roy, M. Iwamura, and B.-G. Kim, “3D Avatar Approach for Continuous Sign Movement Using Speech/Text,” Applied Sciences, vol. 11, no. 8, article 3439, 2021. DOI: 10.3390/app11083439.
7. R. Rastgoo, K. Kiani, S. Escalera, and M. Sabokrou, “Sign Language Production: A Review,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 3451–3461, 2021. DOI: 10.1109/CVPRW53098.2021.00384.
8. [S. Stoll, N. C. Camgoz, S. Hadfield, and R. Bowden, “Text2Sign: Towards Sign Language Production Using Neural Machine Translation and Generative Adversarial Networks,” International Journal of Computer Vision, vol. 128, pp. 891–908, 2020. DOI: 10.1007/s11263-019-01281-2.
2. N. C. Camgoz, O. Koller, S. Hadfield, and R. Bowden, “Sign Language Transformers: Joint End-to-End Sign Language Recognition and Translation,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, pp. 10023–10033. DOI: 10.1109/CVPR42600.2020.01004.
3. S. Tan, N. Khan, Z. An, Y. Ando, R. Kawakami, and K. Nakadai, “A Review of Deep Learning-Based Approaches to Sign Language Processing,” Advanced Robotics, vol. 38, no. 23, pp. 1649–1667, 2024. DOI: 10.1080/01691864.2024.2442721. SQLAlchemy Authors, “SQLAlchemy Documentation.”
4. Z. Yu, S. Huang, Y. Cheng, and T. Birdal, “SignAvatars: A Large-scale 3D Sign Language Holistic Motion Dataset and Benchmark,” in Proceedings of the European Conference on Computer Vision (ECCV), 2024. OpenRouter, “OpenRouter Documentation.”
5. A. Núñez-Marcos, O. Perez-de-Viñaspre, and G. Labaka, “A Survey on Sign Language Machine Translation,” Expert Systems with Applications, vol. 213, article 118993, 2023. DOI: 10.1016/j.eswa.2022.118993. N. Reimers and I. Gurevych, “Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks,” in Proceedings of EMNLP-IJCNLP, 2019, pp. 3982–3992. DOI: 10.18653/v1/D19-1410.
6. D. D. Chakladar, P. Kumar, S. Mandal, P. P. Roy, M. Iwamura, and B.-G. Kim, “3D Avatar Approach for Continuous Sign Movement Using Speech/Text,” Applied Sciences, vol. 11, no. 8, article 3439, 2021. DOI: 10.3390/app11083439.
7. R. Rastgoo, K. Kiani, S. Escalera, and M. Sabokrou, “Sign Language Production: A Review,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 3451–3461, 2021. DOI: 10.1109/CVPRW53098.2021.00384.
8. [S. Stoll, N. C. Camgoz, S. Hadfield, and R. Bowden, “Text2Sign: Towards Sign Language Production Using Neural Machine Translation and Generative Adversarial Networks,” International Journal of Computer Vision, vol. 128, pp. 891–908, 2020. DOI: 10.1007/s11263-019-01281-2.
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